In Pursuit of Greater Reproducibility and Credibility of Early Clinical Biomarker Research.
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ABSTRACT:
SUBMITTER: McShane LM
PROVIDER: S-EPMC5355975 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:High-profile reports of detrimental scientific practices leading to retractions in the scientific literature contribute to lack of trust in scientific experts. Although the bulk of these have been in the literature of other disciplines, environmental toxicology and chemistry are not free from problems. While we believe that egregious misconduct such as fraud, fabrication of data, or plagiarism is rare, scientific integrity is much broader than the absence of misconduct. We are more concerned with more commonly encountered and nuanced issues such as poor reliability and bias. We review a range of topics including conflicts of interests, competing interests, some particularly challenging situations, reproducibility, bias, and other attributes of ecotoxicological studies that enhance or detract from scientific credibility. Our vision of scientific integrity encourages a self-correcting culture that promotes scientific rigor, relevant reproducible research, transparency in competing interests, methods and results, and education. Integr Environ Assess Manag 2019;00:000-000. © 2019 SETAC.
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Project description:Amidst a worldwide vaccination campaign, trust in science plays a significant role when addressing the COVID-19 pandemic. Given current concerns regarding research standards, we were interested in how Spanish scholars perceived COVID-19 research and the extent to which questionable research practices and potentially problematic academic incentives are commonplace. We asked researchers to evaluate the expected quality of their COVID-19 projects and other peers' research and compared these assessments with those from scholars not involved in COVID-19 research. We investigated self-admitting and estimated rates of questionable research practices and attitudes towards current research status. Responses from 131 researchers suggested that COVID-19 evaluations followed partisan lines, with scholars being more pessimistic about others' colleagues' research than their own. Additionally,researchers not involved in COVID-19 projects were more negative than their participating peers. These differences were particularly notable for areas such as the expected theoretical foundations or overall quality of the research, among others. Most Spanish scholars expected questionable research practices and inadequate incentives to be widespread. In these two aspects, researchers tended to agree regardless of their involvement in COVID-19 research. We provide specific recommendations for improving future meta-science studies, such as redefining QRPs as inadequate research practices (IRP). This change could help avoid key controversies regarding QRPs' definition while highlighting their detrimental impact. Lastly, we join previous calls to improve transparency and academic career incentives as a cornerstone for generating trust in science.Supplementary informationThe online version contains supplementary material available at 10.1007/s12144-022-02797-6.
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Project description:Many researchers try to understand a biological condition by identifying biomarkers. This is typically done using univariate hypothesis testing over a labeled dataset, declaring a feature to be a biomarker if there is a significant statistical difference between its values for the subjects with different outcomes. However, such sets of proposed biomarkers are often not reproducible - subsequent studies often fail to identify the same sets. Indeed, there is often only a very small overlap between the biomarkers proposed in pairs of related studies that explore the same phenotypes over the same distribution of subjects. This paper first defines the Reproducibility Score for a labeled dataset as a measure (taking values between 0 and 1) of the reproducibility of the results produced by a specified fixed biomarker discovery process for a given distribution of subjects. We then provide ways to reliably estimate this score by defining algorithms that produce an over-bound and an under-bound for this score for a given dataset and biomarker discovery process, for the case of univariate hypothesis testing on dichotomous groups. We confirm that these approximations are meaningful by providing empirical results on a large number of datasets and show that these predictions match known reproducibility results. To encourage others to apply this technique to analyze their biomarker sets, we have also created a publicly available website, https://biomarker.shinyapps.io/BiomarkerReprod/, that produces these Reproducibility Score approximations for any given dataset (with continuous or discrete features and binary class labels).
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Project description:Clinical trials are the final links in the chains of knowledge and for determining the roles of therapeutic advances. Unfortunately, in an important sense they are the weakest links. This article describes two designs that are being explored today: platform trials and basket trials. Both are attempting to merge clinical research and clinical practice.
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Project description:BACKGROUND:Reproducibility is the hallmark of good science. Maintaining a high degree of transparency in scientific reporting is essential not just for gaining trust and credibility within the scientific community but also for facilitating the development of new ideas. Sharing data and computer code associated with publications is becoming increasingly common, motivated partly in response to data deposition requirements from journals and mandates from funders. Despite this increase in transparency, it is still difficult to reproduce or build upon the findings of most scientific publications without access to a more complete workflow. FINDINGS:Version control systems (VCS), which have long been used to maintain code repositories in the software industry, are now finding new applications in science. One such open source VCS, Git, provides a lightweight yet robust framework that is ideal for managing the full suite of research outputs such as datasets, statistical code, figures, lab notes, and manuscripts. For individual researchers, Git provides a powerful way to track and compare versions, retrace errors, explore new approaches in a structured manner, while maintaining a full audit trail. For larger collaborative efforts, Git and Git hosting services make it possible for everyone to work asynchronously and merge their contributions at any time, all the while maintaining a complete authorship trail. In this paper I provide an overview of Git along with use-cases that highlight how this tool can be leveraged to make science more reproducible and transparent, foster new collaborations, and support novel uses.
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Project description:BackgroundTrauma survivors often have to negotiate legal systems such as refugee status determination or the criminal justice system.Methods & resultsWe outline and discuss the contribution which research on trauma and related psychological processes can make to two particular areas of law where complex and difficult legal decisions must be made: in claims for refugee and humanitarian protection, and in reporting and prosecuting sexual assault in the criminal justice system.ConclusionThere is a breadth of psychological knowledge that, if correctly applied, would limit the inappropriate reliance on assumptions and myth in legal decision-making in these settings. Specific recommendations are made for further study.
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